70,520 research outputs found
Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment
With the evolution of computer systems, the amount of sensitive data to be
stored as well as the number of threats on these data grow up, making the data
confidentiality increasingly important to computer users. Currently, with
devices always connected to the Internet, the use of cloud data storage
services has become practical and common, allowing quick access to such data
wherever the user is. Such practicality brings with it a concern, precisely the
confidentiality of the data which is delivered to third parties for storage. In
the home environment, disk encryption tools have gained special attention from
users, being used on personal computers and also having native options in some
smartphone operating systems. The present work uses the data sealing, feature
provided by the Intel Software Guard Extensions (Intel SGX) technology, for
file encryption. A virtual file system is created in which applications can
store their data, keeping the security guarantees provided by the Intel SGX
technology, before send the data to a storage provider. This way, even if the
storage provider is compromised, the data are safe. To validate the proposal,
the Cryptomator software, which is a free client-side encryption tool for cloud
files, was integrated with an Intel SGX application (enclave) for data sealing.
The results demonstrate that the solution is feasible, in terms of performance
and security, and can be expanded and refined for practical use and integration
with cloud synchronization services
COMTILES: A CASE STUDY OF A CLOUD OPTIMIZED TILE ARCHIVE FORMAT FOR DEPLOYING PLANET-SCALE TILSETS IN THE CLOUD
The container formats commonly used for managing map tiles, such as MBTiles and GeoPackage, were originally designed with only POSIX filesystem access in mind. This makes these file formats inefficient to use in a cloud native environment, especially in combination with large tilesets. The Cloud Optimized GeoTIFF format solves the problem of providing large satellite data in the cloud, creating a new category of so-called cloud optimized data formats. This type of format allows geospatial data to be deployed as a single file on a cheap and scalable cloud object storage such as AWS S3 and accessed directly from a browser without the need for a dedicated backend. Based on the concepts of the COG format, this contribution proposes a new cloud optimized file format called COMTiles, specially designed for planet-scale tilesets. This format has the potential to simplify the deployment workflow of large tilesets in a cloud-native environment, while simultaneously reducing the hosting costs. In comparison to PMTiles, another cloud-optimized tile archive solution, COMTiles can reduce the number of transferred data and the performance of decoding portions of the file. COMTiles also adds support for different coordinate systems
ClouNS - A Cloud-native Application Reference Model for Enterprise Architects
The capability to operate cloud-native applications can generate enormous
business growth and value. But enterprise architects should be aware that
cloud-native applications are vulnerable to vendor lock-in. We investigated
cloud-native application design principles, public cloud service providers, and
industrial cloud standards. All results indicate that most cloud service
categories seem to foster vendor lock-in situations which might be especially
problematic for enterprise architectures. This might sound disillusioning at
first. However, we present a reference model for cloud-native applications that
relies only on a small subset of well standardized IaaS services. The reference
model can be used for codifying cloud technologies. It can guide technology
identification, classification, adoption, research and development processes
for cloud-native application and for vendor lock-in aware enterprise
architecture engineering methodologies
Models in the Cloud: Exploring Next Generation Environmental Software Systems
There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science
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